1. Field of the Invention
Embodiments of the present invention generally relate to contact center agent assignment management and in particular to an improved system and method for assigning an agent to a customer as well as reassigning a customer contact to another agent if an initially matched agent is unable to accept the customer contact.
2. Description of Related Art
Call centers are commonly used by service providers or manufacturers (collectively, “vendors”) to provide customer support. Customers requesting customer support may contact the call center by telephone. As additional methods of communication between agent and contact have been developed, such as e-mail, instant messaging, web chat, and so forth, call centers have evolved into contact centers in order to handle customer contact by a variety of methods, i.e., beyond telephone calls. In contact centers, quickly finding and assigning a well-qualified service agent to service a customer's need is important in providing improved customer satisfaction.
Traditional call centers, like Avaya™ CC-Elite™, route a customer's call to a service agent, having limited information about the customer beyond the telephone number called by the customer (the “called number”), and the telephone number of the customer (the “calling number”). The called and calling numbers are used to route the telephone call to one of several agent queues. The selection of the agent queue may be based upon a relatively simple routing strategy such as the shortest queue or the queue having been idle for the longest time.
The service agent assigned by this simple routing strategy may be ill-equipped to serve the customer, for instance the assigned service agent may not speak the customer's native language, or the assigned service agent may not have the required knowledge to address the customer's problem. This results in an inefficient use of time, the possibility of dropped calls as the customer's call is transferred to another service agent, and caller frustration as the caller is transferred from one service agent to another. In addition, the assigned service agent may be unfamiliar with any prior support calls placed by the customer, resulting in more inefficiency and caller frustration as the caller has to repeat previous support problems to the agent.
More recently deployed call centers may query the caller (e.g., by using interactive voice response (IVR)) about the nature of the call. This information may be used as additional information to route the call. For instance: “Press 1 for English; Press 2 for Spanish;” or “Press 1 for product ‘A;’; Press 2 for product ‘B’” would send the call to different queues with appropriate service agents answering the calls in the queues. This approach does not scale up well when the number of supported products is large, for instance. Although the assigned service agent is more likely to be qualified to help the customer, the assigned service agent may still be unfamiliar with any prior support calls placed by the customer.
Still other contact centers, like those from Genesys™ and heritage-Nortel™, provide contact center administrators with visual routing languages in order to create routing strategies. These routing strategies execute like small functional programs in order to find an appropriate service agent. Routing strategies may use a large amount of knowledge about the customer's contact to find a well-qualified service agent. The knowledge is gathered in a process called “qualification.”
Qualification improves the choice of service agent, but at a greater performance or computing cost of executing the routing strategy. In these systems, the increased cost of choosing a more qualified service agent reduces the ability to scale up the solution. In addition, these systems typically have a small number of instances of routing strategy components. That is, each request for routing is handled by one instance or invocation of a software object or component that handles routing strategy.
Because each such instance or invocation uses a portion of the finite system computing resources available, a resource limitation limits the number of requests serviceable at any point in time. If the chosen service agent cannot serve the call for any reason (e.g., if the service agent is busy wrapping up work on a previous contact, or a different service agent is needed, etc.) the contact is re-queued and a new routing calculation must be made. This lengthens the time needed to respond to the customer.
Each known contact center routing method suffers drawbacks that affects speed of service, relevance of the service agent's skills, or scalability, and thus ultimately customer satisfaction. Therefore, there exists a need for most appropriate service agent to serve the customer's need in a way that can scale to very large numbers of service agents yet can be executed relatively efficiently.